I guess most people have heard of Piketty and his book capital in the twenty-First century. I don't have that book, but the media attention has made me wonder if I could see any trends in Dutch public data. As I progressed with this post, I have conclu... [Read more...]

I saw the post a time series contest on Rob J Hyndman's blog. Since I am still wanting to play around with some bigger data sets, so I went to the source website https://drive.google.com/folderview?id=0BxmzB6Xm7Ga1MGxsdlMxbGllZnM&usp=shar... [Read more...]

Based on The DO loop, since I wanted a fractal Christmas tree and there is no point in inventing what has been made already. Besides, this is not the first time this year that I used R to do what has been done in SAS.Code# http://blogs.sas.com/... [Read more...]

When I downloaded the KNMI meteorological data, the intention was to do something which takes more than just the computers memory. While it is clearly not big data, at the very least 100 years of daily data is not small either. So I took along a load o... [Read more...]

In exercise 61.1 the problem is that the model has bad mixing. In the SAS manual the mixing is demonstrated after which a modified distribution is used to fix the model.In this post the same problem is tackled in R; MCMCpack, RJags, RStan and LaplaceDemon. MCMCpack has quite some mixing ... [Read more...]

I read a post 'race for the warmest year' at sargasso.nl. They used a plot, originating from Ed Hawkins to see how 2014 progressed to be warmest year. Obviously I wanted to make the same plot using R. In addition, I wondered which parts of the year had... [Read more...]

The Royal Netherlands Meteorological Institute has weather information by day for a number of Dutch stations. In this post I want to use those data for a practical problem: when should I switch to winter tires? (or is that snow tires? In any case nails... [Read more...]

In this post I will try to copy the calculations of SAS's PROC MCMC example 61.5 (Poisson Regression) into the various R solutions. In this post Jags, RStan, MCMCpack, LaplacesDemon solutions are shown. Compared to the first post in this series, rcppbugs and mcmc are not used. Rcppbugs has no poisson ... [Read more...]

There are a number of on line efforts to register victims of shootings online. Shootingtracker tries to register all mass shootings, those with four or more victims. Slate had the gun death tally (GDT), gun deaths starting at Newtown, running thro... [Read more...]

This is the last post of testing Laplaces Demon algorithms. In the last algorithms there are some which are completely skipped because they are not suitable for the problem. Reversible Jump is for variable selection. Sequential Metropolis-within-Gibbs,... [Read more...]

This is the third post with LaplacesDemon tuning. same problem, different algorithms. For introduction and other code see this post. The current post takes algorithms Independence Metropolis to Reflective Slice Sampler.Independence MetropolisIndependen... [Read more...]

I am continuing with my trying all algorithms of Laplaces Demon. It is actually quite a bit more work than I expected but I do find that some of the things get clearer. Now that I am close to the end of calculating this second batch I learned that ther... [Read more...]

I was continuing with my Bayesian algorithms in R exercise. For these exercises I port SAS PROC MCMC examples to the various R solutions. However, the next example was logit model and that's just too simple, especially after last week's Jacobian for th... [Read more...]

This is my second post in converting SAS's PROC MCMC examples in R. The task in his week is determining the transformation parameter in a Box-Cox transformation. SAS only determines Lambda, but I am not so sure about that. What I used to do was get an ... [Read more...]

There are many ways to run general Bayesian calculations in or from R. The best known are JAGS, OpenBUGS and STAN. Then some time ago Rasmus Bååth had a post Three ways to run Bayesian models in R in which he mentioned LaplacesDemon (not on CRAN) on top of ... [Read more...]

There was a triathlon in Almere last week, like every year since 1983. I pulled the data of all years to get some idea how things have changed in that sport. To get a visual I decided to plot the best 10% athletes. Then later I decided this was an idea... [Read more...]

Preference mapping is a key technique in sensory and consumer research. It links the sensory perception on products to the liking of products and hence provides clues to the development of new, well tasting, products. Even though it is a key technique,... [Read more...]

I have read about people doing a Bayesian PCA at some points and always wondered how that would work. Then, at some point I thought of a way to do so. As ideas evolved my interest became not PCA as such, but rather in a prefmap. As a first step ... [Read more...]

I got some comments on my priors of last week's post where better priors were proposed. Hence this week's post looks at them. After some minor adaptations, since I have nine beta parameters and beta needs to be fairly high, I can conclude that these pr... [Read more...]

During the last year I have been running some estimations in both JAGS and Stan. In that period I have seen one example where JAGS could not get me decent samples (in the sense of low Rhat and high number of effective samples) but that was data which I... [Read more...]